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Help! My NT Server Is Too Slow |
Abstract
Truth is, most servers do not come already tuned to do the work you need them to do right out of the box. Also, how many companies have trained NT Administrators who can tune servers so that they can provide the best performance for the needs of that company?
For many small shops, this is a big problem. Servers arrive, are set up quickly, go on-line and are never properly tuned for the job they’re expected to do. Another problem is in sizing. If you leave it up to the salesperson, they’re going to get it wrong most of the time unless they have done a thorough job of analyzing the workload of their prospective client’s site. And even if the server is sized correctly, the needs of most companies keep changing. This changes the server’s workload as time goes by.
In the following paper, the Bottleneck theory is used as a way of isolating the factors that are hampering performance in the small server arena. You will also find that I/O is
addressed in depth as it is seen as one of the biggest bottlenecks to SAS System users.
Testing was also done in an effort to try to find ways to increase the performance of small NT Server systems. During the testing some surprises were encountered and are also
presented. Finally, appendices were added to offer some quick tips and to add more information on some of the factors governing performance.
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Solving SAS Performance Problems: Employing Host Based Tools |
Abstract
The SAS® System is composed of a large family of products and solutions, each with varying performance paradigms and machine resource utilization patterns. Today’s greatly increased data scales and heavy use of intensive analytic procedures, coupled with server consolidations placing mixed workloads on shared server and storage are resulting in occasional performance issues.
A previous SAS White Paper, “A Practical Approach to Solving Performance Problems with the SAS System,” detailed the role of the FULLSTIMER option in diagnosing and solving performance problems. It introduced the usage of host-based performance monitors for further investigation. This paper continues with that approach, detailing the use of the most commonly available host-based performance monitors. It will discuss how to employ them in performance testing, interpret them with a SAS mindset, and reconcile them to FULLSTIMER output to determine problem causes.
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Super Size It!!! Maximize the Performance of Your ETL Processes |
Abstract
The success of every business activity—from supplier management to customer service—is dependent upon how well an organization manages its critical data. This paper discusses practical recommendations for optimizing the performance of your Extract, Transform, and Load (ETL) data management processes.
The paper presents best practices in ETL process development and includes performance, tuning, and capacity information. You will learn to analyze and debug ETL flows, gain efficiency quickly, optimize your system environment for performance, and customize with advanced performance techniques.
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ETL Performance Tuning Tips |
AbstractA team of ETL performance experts at SAS Institute reviewed ETL flows for several SAS®9 solutions with the goal of improving the performance and scalability of the solutions. The recommendations that are presented here are based on team observations and performance testing.
A review of concepts that are important to understanding the content of this paper is given at the beginning of the paper, and a Glossary is provided at the end of the paper.
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Large Scale Data Warehousing with the SAS System |
Abstract
Aspects of design, modeling, and physical implementation of data warehouse structures are driven by the volume and data access patterns that are involved. The SAS® System provides excellent scalability for data warehouse structures. There are several key architectural and physical implementation and access issues that must be dealt with to enable the best possible performance. This paper will discuss large data task issues, scalability in data architectures, and how the data can be modeled, stored, and physically I/O managed to achieve the best performance with the SAS® System.
This paper should be of interest to experienced data warehouse practitioners and users, who currently or will work with large scale systems.
An assumption is made that the reader has very basic knowledge pertaining to disk I/O subsystems.
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Efficiency Techniques for Accessing Large Data Files |
Abstract
SAS® software offers the programmer a multitude of ways to enable fast data extraction from large SAS datamarts. The techniques discussed include the use of base SAS software i.e. indexes, Screen Control Language, Structured Query Language, HOLAP techniques for client server architecture and Scalable Performance Data Server component.
This paper discusses some of the extraction options available across the broad spectrumof SAS versions and operating system platforms to minimise overall processing times.
The areas to consider when talking about efficiency techniques include, CPU time, I/O, system memory usage, programming time and disk space.
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Performance Tuning 
